AI’s Impact on Job Market: Software Roles at Risk
“`html
Early Evidence of AI’s Impact on Young Workers’ Employment
As AI tools become more common in peopel’s everyday work, researchers are looking to uncover it’s effects on the job market-especially for early career workers.
A paper from the Stanford Digital Economy Lab, part of the stanford Institute for Human-Centered AI, has now found early evidence that employment has taken a hit for young workers in the occupations that use generative AI the most. as the widespread adoption of AI tools began in late 2022, a split has appeared, adn early-career software engineers are among the hardest hit.
The researchers used data from the largest payroll provider in the United States, Automatic Data Processing (ADP), to gain up-to-date employment and earning data for millions of workers across industries, locations, and age groups. While other data may take months to come out, the researchers published their findings in late August with data through July.
Even though there has been a rise in demand for AI skills in the job market, generative AI tools are getting much better at doing some of the same tasks typically associated with early-career workers. What AI tools don’t have is the experiential knowledge gained through years in the workforce, which makes more senior positions less vulnerable.
These charts show how employment over time compares among early career, developing, and senior workers (all occupations). Each age group is divided into five groups, based on AI exposure, and normalized to 1 in October 2022-roughly when popular generative AI tools became available to the public.
the trend may be a harbinger for more widespread changes,and the researchers plan to continue tracking the data. “it could be that there are reversals in these employment declines. It could be that other age groups become more or less exposed [to generative AI] and have differing patterns in their employment trends. So we’re going to continue to track this and see what happens,” says Bharat Chandra, one of the paper’s authors and a postdoctoral fellow at the Stanford Digital Economy Lab. In the most AI “exposed” jobs,